Method for correction of relative object-detector motion between successive views

ABSTRACT

Registration correction for optical tomographic imaging in three dimensions. An object of interest is illuminated to produce an image. A lateral offset correction value is determined for the image. An axial offset correction value is determined for the image. The lateral offset correction value and the axial offset correction value are applied to the image to produce a corrected file image.

RELATED APPLICATIONS

This application is a continuation-in-part (CIP) of co-pending U.S.patent application Ser. No. 10/126,026, filed Apr. 19, 2002, of Nelson,entitled “Variable Motion Optical Tomography of Small Objects,” which isincorporated herein by this reference.

FIELD OF THE INVENTION

The present invention relates to imaging and, more particularly, todetection of and correction for relative object-detector motion in animaging system where, typically, successive views from differentpositions are acquired, each view representing a two-dimensionalprojection or pseudo-projection of the three-dimensional object.

BACKGROUND OF THE INVENTION

An optical projection tomographic microscopy (OPTM) is suitable forhigh-resolution imaging of a microscopic object, such as a biologicalcell and its nucleus, which are embedded in a fluid medium and containedwithin a microcapillary tube having inner and outer diameters of 40microns and 150 microns, respectively. An OPTM employs a plurality ofviews, each acquired by rotating the object and its containment vesselabout an axis perpendicular to the optical axis and parallel to the axisof the microcapillary tube. A camera, having a CCD image sensor composedof an M×N array of pixels, captures the light after it has passedthrough the object and the imaging optics, which produce a magnifiedimage of the field of view (FOV) on the CCD. Since each view is takenfrom a different perspective, the content of each view will differ fromthe others.

Owing to the extremely small sizes of the components, it can be quitedifficult to position the axis of rotation (typically coincident withthe central axis of the microcapillary tube) in the center of thedetector's FOV. It is further very difficult to hold the microcapillarytube stationary while rotating it. In addition, the cell itself may movealong the tube axis in between views. As a result, each view, which isalready altered due to the tube rotation, can in addition be subject totranslations both axial (parallel to the microcapillary axis) andlateral (perpendicular to the optical axis and to the tube axis). Theselateral translations are in addition to those already present forobjects that are not on the rotation axis.

In order to obtain an accurate 3D reconstruction, whether throughfiltered backprojection or other means, it is therefore necessary tocorrect for the axial motion and for that portion of the lateral motionthat is not due to the changing perspective from one view to another. Itis further necessary to determine where in the detector FOV the axis ofrotation is located.

U.S. Pat. No. 4,858,128, to Nowak describes a method where consecutivescenes are correlated with one another, first in one axis and then,independently, in the other axis. The location of the maximum value forthe two correlations determines the required offset for the two axes.The method described fails to provide means for distinguishing the“natural” lateral translation, due to the change in perspective, fromthe “erroneous” lateral translation, due to translation of themicrocapillary tube. The Nowak patent teaches, “it may be useful toestimate such background component of the signal and to subtract theestimate from the image data.”

William H. Press et al., Numerical Recipes in C: The Art of ScientificComputing, Cambridge University Press; 2nd edition (Jan. 1, 1993)describe means for implementing, via a computer program, the techniquesof cross-correlation between two arrays of data using fast Fouriertransforms (FFTs). In brief, the cross-correlation of two data arrays(such as image data) can be obtained by applying an FFT to each array,multiplying one of the resulting arrays by the complex conjugate of theother, and applying an inverse FFT to the result.

In order to overcome current shortcomings in the state of the art, it isan objective of the present invention to provide a method for findingthe location of the central axis of a microcapillary tube for each viewin a multi-view imaging system. It is a further objective of theinvention to provide a method for detecting relative object-detectormotion between successive views in a multi-view imaging system. It is afurther objective of the invention to provide a method for correctingimage data to remove errors due to object motion during image datacollection. It is a still further objective of the invention to providean imaging system of a type producing a plurality of X-Y data matricesrepresenting projection or pseudo-projection views of an object forsubsequent tomographic reconstruction of axial slices of the object. Thedetected motion may be removed by suitably shifting later data to alignit with earlier data, or vice versa.

SUMMARY OF THE INVENTION

The present invention provides an apparatus and method for registrationcorrection for optical tomographic imaging in three dimensions. Anobject of interest is illuminated to produce an image. A lateral offsetcorrection value is determined for the image. An axial offset correctionvalue is determined for the image. The lateral offset correction valueand the axial offset correction value are applied to the image toproduce a corrected file image.

BRIEF DESCRIPTION OF THE DRAWINGS

While the novel features of the invention are set forth withparticularity in the appended claims, the invention, both as toorganization and content, will be better understood and appreciated,along with other objects and features thereof, from the followingdetailed description taken in conjunction with the drawings describedhereinbelow.

FIG. 1 is a functional block diagram of an example embodiment of amethod for correction of relative object-detector motion betweensuccessive views constructed in accordance with the teachings of thepresent invention.

FIG. 2 is a functional block diagram of a lateral correction portion ofan imaging system employing the example embodiment described in FIG. 1.

FIG. 3 is a functional block diagram of an axial correction portion ofan imaging system employing the example embodiment described in FIG. 1.

FIG. 4A depicts an image of a cell prior to thresholding operations thatare employed in one example of the method of the present invention.

FIG. 4B depicts the result of applying thresholding operations that areemployed in one example of the method of the present invention to theimage shown in FIG. 4A.

FIG. 4C illustrates a histogram showing brightness distributions of theimages shown in FIGS. 4A-4B.

FIG. 5 depicts schematically an optical projection tomographicmicroscopy (OPTM) system employed in one embodiment of the invention.

FIG. 6A and FIG. 6B show one embodiment of an optical tomography systemincorporating a microscope objective lens mounted on a piezoelectrictranslation device is schematically shown.

FIG. 7 shows an example flow diagram illustrating a process foracquiring images used in three-dimensional (3D) image reconstruction ascontemplated by an embodiment of the present invention.

FIG. 8 shows schematically an example of registration correction offsetsfor use in a three-dimensional (3D) image reconstruction as contemplatedby an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The invention is described herein with respect to specific examplesrelating to biological cells, however, it will be understood that theseexamples are for the purpose of illustrating the principals of theinvention, and that the invention is not so limited. Although thepresent invention may be employed in other types of imaging systems,such as, for example, X-ray computed tomography (CT) imaging, forconcreteness of description the following disclosure is directed towardthe invention in the environment of an optical projection tomographicmicroscopy (OPTM) system.

In the discussion that follows, the following assumptions are used whenproviding numerical examples:

1. Each image consists of an array, 640 pixels wide by 480 pixels high;

2. Each pixel contains a single 8-bit (gray level 0 to 255) brightnessvalue;

3. With reference to an OPTM using a microcapillary tube, the tube axisis parallel to the shorter axis (480 pixels);

4. With reference to an OPTM using a microcapillary tube, the tube wallseparation is 530 pixels;

5. The number of bins used in finding the lateral offset (B1) is 20;

6. The number of bins used in finding the axial offset (B2) is 2;

7. The array is zero-padded to 1024 by 1024 pixels.

It is to be understood that these numerical values are for illustrativepurposes only; other numerical values may be employed without detractingfrom the nature of the invention.

Referring now to FIG. 1, a functional block diagram of an exampleembodiment of a method for correction of relative object-detector motionbetween successive views constructed in accordance with the teachings ofthe present invention is shown. In the example embodiment, an alteredcopy of each image is generated, in which the brightest pixels arereassigned a brightness level of zero, while all other pixels retain thesame brightness as in the initial image. A two-dimensional (2D) FFT ofthis thresholded image is then multiplied, pixel-by-pixel, with thecomplex conjugate of the 2D FFT of a reference image. The brightness ofthe resulting array is then summed along each line parallel to the axisof the microcapillary tube (to be referred to henceforth as the Y axis)to develop a one-dimensional (1D) array containing information about thebrightness pattern in the direction (to be referred to henceforth as theX axis) perpendicular to the optical axis and to the microcapillaryaxis. A 1D FFT is then applied, and the location of the maximum isdetermined. The location determines the amount of offset to be appliedalong the X axis in order to bring the image of the microcapillarytube's center axis to its desired position in the image.

The reference image takes advantage of the constancy of the separationbetween the walls of the microcapillary tube, and consists of twomaximally bright lines separated by the known amount found in theacquired images; the rest of the reference image has zero brightness.The tube walls appear only faintly in the pseudo-projection images, asthe refractive indices of the tube walls are matched with materialsinside the tube and between the tube and the slide/coverslip assembly.The effect of the histogram operation is to enhance the contrast betweenthe tube walls and the rest of the image. Using the pre-determined tubewall separation, in combination with the known number of pixels alongthe X axis of the image, makes it possible to distinguish the movementof the tube itself from the movement of the objects within the tube, dueto the rotation of the tube and the consequent perspective change. Bycross-correlating the two images based on a constant feature, our methodminimizes the possibility of tracking the movements of changing featureswithin the cell.

A cross-correlation method is used to determine the amount of the axialoffset from the Y-axis. To do so, a copy of the original image is againthresholded, but using different criteria for determining which pixelsare reset to zero brightness. A 2D FFT is applied to this image, andmultiplied, pixel-by-pixel, with the complex conjugate of the 2D FFT ofthe thresholded image derived from the immediately preceding view. A 2DFFT is applied to the result, and the X-axis offset is determined as themaximum in the cross-correlation function along the line thatcorresponds to the difference in the lateral correction of the currentimage with that of the previous image. This is a distinction fromprevious methods, in that the X-axis is constrained by the Y-axisoffset; it is not found independently of the Y-axis offset.

Unlike the lateral correction, the axial correction is an iterativeprocess and thus is subject to cumulative errors. The axialcross-correlation functions effectively, however, as long as the changein perspective between consecutive images is not too large; thiscorresponds to small angular increments in the rotation. By keeping theangular increment small, the spatial content does not vary by much,allowing the cross-correlation to track similar features in each image.Since the angular increment also determines the lateral resolution ofthe 3D tomographic reconstruction, the requirement that the angularincrement be kept small to allow the cross-correlation to work well isnot an onerous one.

Briefly stated, this embodiment of the present invention removes theeffects of axial and lateral movement by the microcapillary tube bysuitably shifting subsequent images to align them with previous images,or vice versa. Cross-correlation methods are used to find the offset onthe lateral axis, then on the tube axis, with the restriction that thepeak correlation for the axial movement must come after thedetermination of the lateral movement.

The first step 111 is to generate the binary template image. Two whitelines having, for example, a grayscale level of 65,535, are created attheir ideal positions. Each line has a length of 480 pixels, runningparallel to the short image dimension. The locations of the two linesare determined by the long image dimension (640 pixels) and the tubewall separation, empirically determined as 530 pixels. The first line islocated at line 0 and the second line is located at line 530. In thisembodiment, the size of the template image may be expanded from 640×480to 1024×1024 to provide zero-padding in both dimensions; however, thisaction is not essential to the invention.

A 2D FFT is performed on the template image so that real and imaginarycomponents are saved in alternating indices of the resulting array.Thus, for a zero-padded array, the array size is 2048×1024. The templateimage is now in a form ready for use.

At step 114 the lateral offset is found. In step 114, the image isthresholded in order to black out the background pixels, and thencross-correlated with the binary image of two bright lines. Images ofinterest are subject to the lateral offset determination 114. Thedifference between the lateral correction 114 of the current image andthat of the previous image is also saved for use in the axial correction115.

Referring now to FIG. 2, a functional block diagram of a lateralcorrection portion of an imaging system employing the example embodimentdescribed in FIG. 1 is shown. The steps involved in finding the lateraloffset 114 include constructing a grayscale histogram of the image,where the number of bins (B1) may be set at any integer value from 2 to255. For the present example, it is assumed that B1=20. The bin with thegreatest number of pixels is found (except the first bin, correspondingto the darkest pixels), and all pixels in the original image having thatbin's grayscale value or higher are set equal to zero in a copy of theoriginal image. The effect of this procedure 21 is to remove thebackground pixels from further consideration in order to produce athresholded image.

As an example, suppose the input image has minimum and maximum grayscalevalues of 31 and 190, respectively, so that each bin has a width ofeight gray levels [(1+190+31)/20=8]. Now further suppose that peak inthe histogram occurs at bin #16 (i.e., gray levels from 151 to 158).Then the thresholded image will be similar to the original image, exceptthat all pixels with an initial gray level greater than 150 now have agray level of zero.

FIGS. 4A-4C illustrate the effect of applying these steps 21 to animage. A visual comparison of an original image to a segmented image maybe made with reference to FIG. 4A, which shows an example of a cellimage prior to segmentation and thresholding, and then to FIG. 4B whichshows an example of a segmented and thresholded cell image correspondingto the original image of FIG. 4A. FIG. 4C is a histogram of an exampleimage showing a comparison of the grey levels of the original image andthe image after thresholding is applied.

A 2D FFT is applied to the thresholded image 22, and its Fouriertransform is multiplied 23 by the complex conjugate of the Fouriertransform of the template image. The resulting array is summed 24 alongeach of the 640 rows to compute a new array, which is Fouriertransformed (in ID) 25 to find the cross-correlation of the rows of thethresholded image and the reference image. The maximum value of the IDarray is located 26 and evaluated 28. The position of the maximum isdesignated as D_(LAT) and its magnitude is designated as C_(MAX).

The necessary offset is determined by the difference between D_(LAT) andits ideal position of 55 [(640−530)/2=55]. Thus, for example, ifD_(LAT)=63, then an upward shift of 8 pixels is necessary (63−55=8),while if D_(LAT)=41, then a downward shift of 14 pixels (55−14=14) isrequired.

The procedure 114 is repeated for all images in the data set. Note thateach image is referenced to the same template, so there is no cumulativeerror. To assist in the axial correction, D_(LAT) is saved 29 for eachimage.

Referring now to FIG. 3, a functional block diagram of an axialcorrection portion of an imaging system employing the example embodimentdescribed in FIG. 1 is shown. The axial correction 115 is performed onall images except the first. A copy of the input image is thresholded atstep 31, and then cross-correlated with a thresholded copy of theprevious image. The offset is determined as the maximum in thecross-correlation function along the line that corresponds to thedifference in the lateral correction for the current perspective[D_(LAT)(N)] and the lateral correction for the immediately precedingperspective [D_(LAT)(N−1)]. Unlike the lateral correction 114,therefore, the axial correction 115 is an iterative process and thus issubject to cumulative errors.

A copy of the input image is thresholded 31 in the same manner as forthe lateral correction, but in this case the number of bins in thehistogram is B3. In the present example, B3=2. Thus, all pixels with agray level greater than the mid-range gray level are set to zero, whilethose with lower gray levels retain their initial values. For example,an input image with minimum and maximum values of 31 and 190,respectively, will result in a thresholded image identical to theinitial one, except that all pixels that were initially brighter than110 are now zero.

Having thus blacked out the bright pixels, the thresholded image isFourier-transformed in 2D 32. It is then filtered 33 to eliminate thesmallest features, which may produce spurious peaks on the crosscorrelation. Only spatial frequencies up to 102 cycles/pixel,corresponding to feature sizes of ten pixels or less, are multiplied andpixels at higher spatial frequencies are set to zero. The resultingarray is saved 34 as S_(N) and multiplied 35 by the complex conjugate ofS_(N−1), obtained from the preceding image's thresholded copy. A 2D FFTis next applied to the resulting array to find the cross-correlation ofthe two consecutive, thresholded, low-pass-filtered images. Thedifference in the lateral offset between the two consecutive images[D_(LAT)(N)−D_(LAT)(N−1)] found from the lateral correction step 114 isnecessary now, since it is incorrect to find the global maximum of thecorrelation array. Instead, a local maximum, F_(MAX), must be found inthe row that corresponds to [D_(LAT)(N)−D_(LAT)(N−1)]. The columncontaining F_(MAX) is designated G_(MAX). If G_(MAX) is greater thanhalf the padded image dimension (1024, in this example), then its valuesignifies a negative shift, relative to the preceding image, having amagnitude equal to the zero-padded dimension minus the value of G_(MAX).If G_(MAX) is less than half the zero-padded dimension, then therequired shift, relative to the preceding image, is positive and equalto G_(MAX).

As an example, suppose D_(LAT)(N−1)=45, while D_(LAT)(N)=63. ThenF_(MAX) will be found on row 18 of the correlation array (63−45=18). IfF_(MAX), the maximum value of row 18, occurs in the fifth column, thenG_(MAX)=5 and the image must be shifted five pixels to the left of theprevious image. If the maximum occurs at row 1019 (G_(MAX)=1019), thenthe image must be shifted five pixels to the right (1024−1019=5) of theprevious image, since 1019 is greater than 512.

After G_(MAX) is found, the value of the shift is added to the sum ofall the previous axial offsets to determine D_(AXIAL), the cumulativedifference from the first acquired image to the current image. The shiftmay be positive or negative; hence, some images may not require anyaxial shift. For each image, four values are written to a text file:

1. The position of the upper tube wall, D_(LAT);

2. C_(MAX), the maximum value of the cross-correlation between thecurrent image and the reference image;

3. G_(MAX), the location of F_(MAX) on the appropriate row of thecross-correlation between the current image and the previous image (forthe first image, G_(MAX)=0);

4. F_(MAX) (for the first image, F_(MAX)=0).

The corrected file is generated by cropping the appropriate number ofpixels from one or two edges and shifting the remaining pixels by thenumber cropped. To maintain the original image dimensions (640×480), thespaces at the opposite edges from the cropped edges are replaced bypixels set to the maximum gray level of the original image.

For example, suppose that for one of the images, the maximum gray levelis 229, D_(LAT)=63, D_(AXIAL)=29, and G_(MAX)=1022. Then the pixels inthe top eight rows (63−55=8) and the left 27 columns (29−1024+1022=27)are deleted from the image. Thus the ninth row of column 28 occupies theupper left corner. Eight rows are added to the bottom of the image, and28 columns are added to the right of the image; these pixels have graylevels of 229. When these procedures are complete, the 632×453-pixelregion in the upper left of the corrected image is identical to the632×453-pixel region in the lower right of the original image. Bothimages have dimensions of 640×480.

Another example embodiment incorporates only the axial correction 115and the writing of the corrected image 116. This embodiment is usefulwhen the walls of the microcapillary tube are not visible and the tube'slateral motion is known to be negligible

In yet another embodiment, the tube wall separation is calculatedautomatically from the first view (N=0). Otherwise it is identical tothe embodiment described hereinabove with reference to FIGS. 1-3. Inanother embodiment of the invention, the separation of the tube walls isdetermined based on a calculation of their separation in one or more ofthe images. This is accomplished by using as a reference an imagederived from a single bright line, as by a 2D FFT and a complexconjugation. The rows are summed, as in the first embodiment, and thelocation of the maximum is taken as the location of one wall of the tuberelative to its location in the image from which the reference image wasderived. The location of the next highest correlation value gives thelocation of the other tube wall, relative to the first. If desired, thesearch for this secondary maximum can be restricted to a range whosecentral location, relative to the first tube wall, is in the vicinity ofthe presumed tube width. This embodiment also encompasses thepossibility of using the single-line reference for all the acquiredviewpoints. Such an arrangement may be useful when the tube wallseparation is not known, or when the tube's inner walls do not form acircle, as when the tube's inner profile is square is elliptical.

In another embodiment of the invention, the characteristics of thethresholding step may vary based on feedback from the correlation. Suchiterative approaches may be employed in the first thresholding step forthe lateral correction, in the second thresholding step for the axialcorrection, or in both. One characteristic that may be varied is thenumber of divisions or bins used in the histogram. Anothercharacteristic that can be varied is the number of gray levels containedwithin each histogram bin. For example, the histogram may be based onthe square root of the brightness level.

According to a feature of the invention, the output of the method is acropped copy of the input file, with the uncropped portions shiftedvertically and/or horizontally, and with additional blank pixelsinserted at one or two of the borders to retain the input image size.

According to a further feature of the invention, the results of themethod employed are saved to a digital file, which may be altered andedited using computer word-processing applications. The altered textfile may then be used to generate the offsets in the two axes, thusbypassing many of the calculations described above. In this embodiment,the lateral correction procedure of steps 114 through 116 is iterated tofind the maximum of C_(MAX). If C_(MAX) has a magnitude less than acritical value C_(CRIT), then the entire procedure is repeated, startingwith the thresholding 27, but with the number of bins in the histogramchanged from B1 to B2. C_(MAX) is again located 26 and evaluated 28.

Referring now to FIG. 5, there shown schematically is an exampleillustration of cells packed into a capillary tube as contemplated by anembodiment of the present invention. In this example embodiment, asection of the capillary tube 3 is filled with objects of interest 1,such as cells, that are packed rigidly into the tube. Each of the cellsmay include a nucleus 2. The capillary tube 3 has a central axis 4oriented with reference to a coordinate system 6 having coordinates inthe x, y and z-directions. In some instances, at least one molecularprobe 153 may be bound within the cell. A computer 7 is coupled toprovide control signals to a rotational motor 5 and a translationalmotor 8. It will be recognized that equivalent arrangements of one ormore motors, gears or fluidics or other means of generating motion mayalso be employed to achieve the necessary translational and rotationalmotion of the capillary tube or other substrate. In some cases, one ormore of the motors may be replaced by manual positioning devices orgears or by other means of generating motion such as hydraulic orpiezoelectronic devices. The axis of translation is the z-axis, androtation is around the z-axis. The positioning motor 9 is coupled tomove the cell in a plane defined by the x, y-axes, substantiallyperpendicular to the central axis for the purpose of centration, asnecessary.

It will be recognized that the curved surface of the capillary tube willact as a cylindrical lens and that this focusing effect may not bedesirable in a projection system. Those skilled in the art willappreciate that the bending of photons by the tube can be eliminated ifthe spaces between the point source and the tube and between the tubeand the detector surfaces are filled with a material 10 whose index ofrefraction matches that of the capillary tube and that the tube can beoptically coupled (with oil or a gel, for example) to the space fillingmaterial.

Consider the present example of cells packed into a capillary tube. Thecells may preferably be packed single file so that they do not overlap.The density of packing whole cells of about 100 microns in diameter intoa capillary tube with diameter less than 100 microns can be roughly 100cells per centimeter of tube length. For bare nuclei of about 20 micronsin diameter, the packing can be roughly 500 nuclei per centimeter oftube length where the tube diameter is proportional to the object size,about 20 microns in this case. Thus, within several centimeters ofcapillary tube length, a few thousand non-overlapping bare nuclei can bepacked. By translating the tube along its central axis 4, motion in thez-direction can be achieved. Moving the tube in the x, y-directionsallows objects within the tube to be centered, as necessary, in thereconstruction cylinder of the optical tomography system. By rotatingthe tube around its central axis 4, a multiplicity of radial projectionviews can be produced. Moving the tube in the z-direction with constantvelocity and no rotation simulates the special case of flow opticaltomography.

One advantage of moving a tube filled with cells that are otherwisestationary inside the tube is that objects of interest can be stopped,then rotated, at speeds that permit nearly optimal exposure for opticaltomography on a cell-by-cell basis. That is, the signal to noise ratioof the projection images can be improved to produce better images thanmay be usually produced at constant speeds and direction typical of flowsystems. Objects that are not of interest can be moved out of theimaging system swiftly, so as to gain overall speed in analyzing cellsof interest in a sample consisting of a multitude of cells.Additionally, the ability to stop on an object of interest, then rotateas needed for multiple projections, nearly eliminates motion artifacts.Still further, the motion system can be guided at submicron movementsand can advantageously be applied in a manner that allows sampling ofthe cell at a resolution finer than that afforded by the pixel size ofthe detector. More particularly, the Nyquist sampling factor of 2 couldbe managed by the motion system moving in increments that fill half apixel width, for example. Similarly, the motion system can compensatefor the imperfect fill factor of the detector.

Referring now to FIG. 6A, there shown is a close-up view of a singlespecimen, as for example a single cell, immersed within a medium ofoptical indexing material. The single specimen is shown within amicro-capillary tube 3 (e.g. one such tube is manufactured by PolymicroTechnologies, LLC., AZ, US) that can be rotated for taking multipleprojections and an objective lens 40 that can be axially scanned isschematically shown. An illumination source includes a light source 50that projects light through an aperture 51, a stop 52, and through acondenser lens 53 that is positioned before a microscope slide 54. Amicro-capillary tube 3 holds a cell 1 between the slide and a thincoverslip 55. An objective lens 40, preferably an oil-immersion lens, isdisposed to receive light passed through the micro-capillary tube 3. Theobjective lens is translated along the optical axis by an actuator 57such as a piezoelectric element. The coverslip 55 must be thin enough sothat the distance between the center of the micro-capillary tube and theouter surface of the coverslip is smaller than the working distance ofthe objective lens. The condenser lens 53 is within the index ofrefraction n, (e.g. air). The slide 54 and coverslip 55 have index ofrefraction n₂. A region 58 surrounding the micro-capillary tube 3contains index-matching medium 15 such as optical gel or immersion oil,which has index of refraction n₃. The micro-capillary tube 3 itself hasindex of refraction n₄. The region 59 surrounding the cell 1 within themicro-capillary tube contains a medium 10 possessing an index ofrefraction n₅. A region 60 within the cell may be filled with the samemedium 10, or may differ in its index of refraction n₆. It is preferredthat n₃=n₄=n₅=n₆ (differences must be minimized) between the two flatparallel surfaces formed by slide 54 and coverslip 55 to avoid acylindrical lens distortion. The image is projected onto a camera 43.

Referring now to FIG. 6A and FIG. 6B, one embodiment of an opticaltomography system employed in the present invention, incorporating amicroscope objective lens mounted on a piezoelectric translation deviceis schematically shown. The piezoelectric transducer 57 is used to movean objective lens 60 an axial distance of about 40 microns or more. Inone useful embodiment, a micro-objective positioning system provides asuitable actuator 57, which is driven up and down along the z axis oftube coordinate system 6. In this embodiment, it may be used with a highnumerical aperture objective, mounted on an standard transmissionmicroscope 64 with a video camera 43 attached and a computer-controlledlight source and condenser lens assembly 61. The computer-controlledcondenser and light source 50 may advantageously be a light sourceincluding one or more incandescent bulbs, an arc lamp, a laser, or alight emitting diode. Computer control signals 70 are linked to thecomputer-controlled condenser and light source 50 for controlling lightmodulation.

The output from the camera 43 is stored in a computer memory 72. Amicrocapillary tube 3 containing the specimen can be translated alongthe x or y axes of tube coordinate system 6. In addition, themicrocapillary tube 3 can be rotated about its “θ” axis 49, via arotational motor 5 that can be computer-controlled. As used hereinmicro-capillary tube is defined as a capillary tube having a diameterwhere the field of view for microscopic imaging is comparable to thecapillary tube diameter. In an example embodiment the rotational motor 5is controlled by control signals 71 as provided by the computer 7. Forhigh speed applications other controls may be added in order to reducevibrations during an axial scan. The acquired image may be displayed onmonitor 73.

Referring now to FIG. 7, an example flow diagram illustrating a processfor acquiring images used in three-dimensional (3D) image reconstructionas contemplated by an embodiment of the present invention is shown. Ascontemplated by one example of the present invention, a 3D imagereconstruction process includes the steps of loading the tube packedwith cells at step 81, translating the tube until the first cell ofinterest has been located at step 82, centering the cell of interest, asnecessary, at step 83, generating a set of projections at each differentrotation angle at step 84, determining when the data set is complete atstep 85, and repeating the process from steps 82 through 85 until allcells of interest have been scanned. At step 86 registration correctionsare made. The process may be implemented in a computer software programexecuted by a personal computer such as computer 7, for example.

Referring now to FIG. 8, there shown schematically is an example ofregistration correction offsets for use in a three-dimensional (3D)image reconstruction as contemplated by an embodiment of the presentinvention. Registration correction is applied to find the lateralposition of an object of interest 1, such as a cell or nucleus 2,contained in a capillary tube 3 having a capillary tube wall 62. Thelateral offset is the error along the longer image dimension (640pixels), perpendicular to the tube axis, Z. The axial offset is theerror along the shorter image dimension (480 pixels), parallel to thetube axis Z. The object of interest 1 has a lateral position LP and anaxial position AP. As images are acquired from various points of view,registration correction is applied in order to allow reconstruction ofthe object of interest with identical features maintained in the sameplane in the various views.

1. A method for correction of relative object-detector motion betweensuccessive views comprising the steps of: illuminating an object ofinterest to produce an image; determining a lateral offset correctionvalue for the image; determining an axial offset correction value forthe image; and applying the lateral offset correction value and theaxial offset correction value to the image to produce a corrected fileimage.
 2. The method of claim 1, wherein the step of determining alateral offset correction value for the image further comprises thesteps of: thresholding the image; and cross-correlating the image with atemplate image.
 3. The method of claim 2, wherein the template image iscreated by a method comprising the steps of: creating at least two whitelines at predetermined positions to form a preliminary template image;expanding the preliminary template image to provide zero-padding in twodimensions resulting in an expanded template image; and performing atwo-dimensional FFT on the expanded template image to create the finaltemplate image.
 4. The method of claim 2, wherein the steps ofthresholding the image and cross-correlating the image further comprisethe steps of: finding the grayscale histogram of the image including aplurality of bins; identifying a bin with the greatest number of pixels;setting all pixels in the image having that bin's grayscale value orhigher equal to zero in a copy of the image; applying a two-dimensionalFFT to the copy of the image to produce a Fourier transform; multiplyingthe Fourier transform by a complex conjugate of the Fourier transform ofthe template image to produce a new image array; summing the new imagearray, along each of the plurality of rows to compute a lateral sumarray; computing a one dimensional Fourier transform of the lateral sumarray to find the cross-correlation of the rows of the copy of theoriginal image and the template image; setting an uncorrected positionof the upper tube wall, at the location of the maximum value of thelateral sum array; and determining the lateral offset as the differencebetween the uncorrected position of the upper tube wall and apredetermined wall edge position.
 5. The method of claim 1, wherein thestep of determining an axial offset correction value for the imagefurther comprises the steps of: thresholding the image;cross-correlating the image with the thresholded version of a previousimage; and determining an axial offset as a maximum in thecross-correlation function along the line that corresponds to thedifference in the lateral corrections of the two images.
 6. The methodof claim 1, wherein the step of determining an axial offset furthercomprises the steps of: finding the grayscale histogram of the imageincluding a plurality of bins; identifying a bin with the greatestnumber of pixels; setting all pixels in the original image having thatbin's grayscale value or higher equal to zero in a copy of the originalimage; applying a low-pass filter to the thresholded image; computing across-correlation of the thresholded, low-pass filtered image with apreceding image's thresholded, low-pass filtered version; finding themaximum correction value in the row of the resultant cross-correlationthat corresponds to the difference in the two images' lateral offsets;and adding the correction value to the sum of all the previous axialoffsets.
 7. The method of claim 1 further comprising the steps of:writing the value of the lateral offset to a file; writing the value ofthe array element used to determine the lateral offset to a file;writing the value of the axial offset to a file; writing the value ofthe array element used to determine the axial offset to a file; andgenerating a corrected image by cropping the appropriate number ofpixels from one or two edges and shifting the remaining pixels by thenumber cropped.
 8. The method of claim 1, wherein the object of interestis a cell or a cell nucleus.
 9. The method of claim 4, furthercomprising the step of repeating the steps with a different number ofbins in the histogram, if the maximum value of the cross-correlation hasa magnitude less than a predetermined value.
 10. Apparatus forcorrecting positioning and motion errors in an imaging system,comprising: means for acquiring at least two views of an object; said atleast two views including M rows and N columns of image brightness data;means for comparing a pattern of image brightness data from eachacquired view with a corresponding reference pattern of image brightnessdata to produce two coefficients “A” and “B” containing informationabout a similarity therebetween; said means for comparing includes:first means for producing a modified copy of said acquired image inwhich an alteration of brightness level is applied to pixels havingbrightness levels within a specified range; second means for performinga cross-correlation between said modified copy of the acquired view withsaid reference view; third means for locating and evaluating the maximumof the resulting cross-correlation function, the row or column wheresaid maximum is located determining the value of coefficient “A”; fourthmeans for producing modified copies of said acquired images in which analteration of brightness level is applied to pixels having brightnesslevels within a specified range; fifth means for performing across-correlation between two said modified copies of consecutiveacquired images; sixth means for locating and evaluating the restrictedmaximum of the resulting cross-correlation function, said restrictionbeing that the row or column on which said restricted maximum is locatedmust be orthogonal to and intersect the row or column on whichcoefficient “A” is located; location of said restricted maximumdetermining coefficient “B.”
 11. A method according to claim 10, furthercomprising means responsive to said values of said coefficients “A” and“B” for shifting the acquired views in two orthogonal directions, thedirections and magnitudes of said amounts being related to said valuesof said coefficients “A” and “B.”
 12. A method according to claim 10, inwhich the means for cross-correlating to determine coefficient “A”includes the step of summing the rows or columns to obtain aone-dimensional array, said summation being performed in a directionorthogonal to the direction of the shift whose magnitude is determinedby said coefficient “A.”
 13. A method according to claim 10 in which thereference pattern comprises an array of M rows and N columns of imagebrightness data in which all pixels, with the exception of one or morerows or columns, have the same brightness value, said one or more rowsor columns having a brightness that is uniform, but substantiallydifferent than the other pixels.
 14. A method according to claim 10 inwhich the reference pattern comprises an array of M rows and N columnsof image brightness data in which all pixels, with the exception of twogroups consisting of one or more rows or columns, have the samebrightness value, said two groups having a brightness that is uniform,but substantially different than the other pixels, and having aseparation that corresponds to the apparent separation of the opposingwalls of a microcapillary tube, said opposing walls both appearing inthe field of view of a succession of two or more images, saidmicrocapillary tube containing an object of interest.
 15. A methodaccording to claim 10 in which the object of comprises a biological cellor nucleus.
 16. A method according to claim 10 including means ofrepeating the steps of thresholding, cross-correlation, and locating andevaluating the maximum of said cross-correlation, said repetitioncomprising means of finding the maximum value of the maximum correlationbased on multiple thresholding.
 17. A method according to claim 14 inwhich the separation of the two groups or rows or columns is computedbased on one or more acquired images.
 18. A method for three dimensional(3D) reconstruction of an object of interest, comprising the steps of:(a) packing a set of objects of interest into a linear container; (b)illuminating at least at least one object of the set of objects ofinterest with at least one optical projection beam; (c) translating thelinear container until the at least one object is located within aregion of the at least one optical projection beam; (d) centering the atleast one object as necessary; (e) rotating the at least one objectthrough a plurality of radial angles; (f) generating a set of projectionimages at each radial angle of the plurality of angles; (g) repeatingthe steps (b) through (f) until the set of objects of interest (1) hasbeen scanned; and (h) correcting motion of the scanned objects ofinterest by determining a lateral offset correction value for thescanned image, determining an axial offset correction value for thescanned image, and applying the lateral offset correction value and theaxial offset correction value to the scanned image to produce acorrected file image.
 19. The method of claim 18, wherein the at leastone object is a cell or a cell nucleus.
 20. The method of claim 18,wherein the step of packing a set of objects of interest into a linearcontainer comprises the steps packing a plurality of cells into amicrocapillary tube.
 21. A method for correction of relativeobject-detector motion between successive views comprising the steps of:imaging an object of interest to produce an image; determining an axialoffset correction value for the image, wherein the step of determiningan axial offset correction value for the image further includes thesteps of: thresholding the image, cross-correlating the image with thethresholded version of a previous image, and determining an axial offsetas a maximum in the cross-correlation function along the line thatcorresponds to the difference in the lateral corrections of the twoimages; and applying the lateral offset correction value and the axialoffset correction value to the image to produce a corrected file image.22. The method of claim 1 wherein a plurality of images are produced togenerate an input image file and a plurality of corrected file imagesare a cropped copy of the input image file, with uncropped portionsshifted vertically and/or horizontally, and with additional blank pixelsinserted at one or two of the borders to retain the input file imagesize.
 23. The method of claim 1 wherein the corrected file imagescomprise calculated offset values saved to a digital file.
 24. Themethod of claim 23 wherein the calculated offset values are processedusing computer word-processing to produce an altered text file, and thealtered text file is used to generate offsets in two axes, and whereinthe step for determining a lateral offset correction value for the imageis iterated to find a maximum value.
 25. The method of claim 22 whereinthe calculated offset values comprise: a position of a maximum value ofthe cross-correlation between a current image and the template image; amaximum value of the cross-correlation between a current image and thetemplate image; a location of a maximum correlation value on thecorresponding row of a cross-correlation between the current image andthe previous image; and a maximum value of the cross-correlation betweena current image and a preceding image.